Literature DB >> 32506698

Supply Constraint from Earthquakes in Japan in Input-Output Analysis.

Michiyuki Yagi1, Shigemi Kagawa2, Shunsuke Managi3, Hidemichi Fujii2, Dabo Guan4.   

Abstract

Disasters often cause exogenous flow damage (i.e., the [hypothetical] difference in economic scale with and without a disaster in a certain period) to production ("supply constraint"). However, input-output (IO) analysis (IOA) cannot usually consider it, because the Leontief quantity model (LQM) assumes that production is endogenous; the Ghosh quantity model (GQM) is considered implausible; and the Leontief price model (LPM) and the Ghosh price model (GPM) assume that quantity is fixed. This study proposes to consider a supply constraint in the LPM, introducing the price elasticity of demand. This study uses the loss of social surplus (SS) as a damage estimation because production (sales) is less informative as a damage index than profit (margin); that is, production can be any amount if without considering profit, and it does not tell exactly how much profit is lost for each supplier (upstream sector) and buyer (downstream sector). As a model application, this study examines Japan's largest five earthquakes from 1995 to 2017 and the Great East Japan Earthquake (GEJE) in March 2011. The worst earthquake at the peak tends to increase price by 10-20% and decrease SS by 20-30%, when compared with the initial month's prices/production. The worst damage tends to last eight months at most, accumulating 0.5-month-production damage (i.e., the sum of [hypothetical] differences in SS with and without an earthquake [for eight months] is 50% of the initial month production). Meanwhile, the GEJE in the five prefectures had cumulatively, a 25-month-production damage until the temporal recovery at the 37th month.
© 2020 Society for Risk Analysis.

Entities:  

Keywords:  Earthquakes in Japan; input-output analysis; supply constraint

Year:  2020        PMID: 32506698      PMCID: PMC7818455          DOI: 10.1111/risa.13525

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  6 in total

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